Finite element analysis of electroactive and magnetoactive coupled behaviors in multi-field origami structures

Wei Zhang, Saad Ahmed, Sarah Masters, Jonathan Hong, Zoubeida Ounaies, Mary Frecker

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Active origami-inspired designs, which incorporate active materials such as electroactive polymers and magnetoactive elastomers into self-folding structures, have shown good promise in engineering applications. In this article, finite element analysis models are developed for several bending and folding configurations that incorporate a combination of active and passive material layers, such as electroactive polymer–actuated unimorph benders based on single and multilayer electroactive polymers, electroactive polymer–actuated notched unimorph folding configurations, and a multi-field actuated bimorph configuration. Constitutive relations are developed for both electrostrictive and magnetoactive materials to model the coupled behaviors explicitly. Shell elements are adopted for their capacity of modeling thin films, relatively low computational cost, and ability to model the intrinsic coupled behaviors in the active materials under consideration. The electrostrictive coefficients are measured and then used as input in the constitutive modeling of the coupled behavior. The magnetization of the magnetoactive elastomer is measured and then used to calculate the magnetic torque as a function of the special orientation, which leads to spatial deformation of the magnetoactive elastomers. The objective of the study is to validate the constitutive models implemented through the finite element analysis method to simulate multi-field coupled behaviors of the active origami configurations. Through quantitative comparisons, simulation results show good agreement with experimental data. By investigating the impact of material selection, location, and geometric parameters, this finite element analysis approach can be used in design of self-folding structures, reducing trial-and-error iterations in experiments.

Original languageEnglish (US)
Pages (from-to)3983-4000
Number of pages18
JournalJournal of Intelligent Material Systems and Structures
Issue number20
StatePublished - Dec 1 2018

All Science Journal Classification (ASJC) codes

  • General Materials Science
  • Mechanical Engineering


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